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Recurrent Models and Examples with MXNetR

Recurrent Models and Examples with MXNetR

As a new lightweight and flexible deep learning platform, MXNet provides a portable backend, which can be called from R side. MXNetR is an R package that provide R users with fast GPU computation and state-of-art deep learning models. In this post, We have provided several high-level APIs for recurrent models with MXNetR. Recurrent neural network (RNN) is a...

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An Introduction to XGBoost R package

Introduction XGBoost is a library designed and optimized for boosting trees algorithms. Gradient boosting trees model is originally proposed by Friedman et al. The underlying algorithm of XGBoost is similar, specifically it is an extension of the classic gbm algorithm. By employing multi-threads and imposing regularization, XGBoost is able to utilize more computational power and get more accurate prediction. Please...

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Introduction to XGBoost R package

Introduction to XGBoost R package

Introduction XGBoost is a library designed and optimized for boosting trees algorithms. Gradient boosting trees model is originally proposed by Friedman et al. The underlying algorithm of XGBoost is similar, specifically it is an extension of the classic gbm algorithm. By employing multi-threads and imposing regularization, XGBoost is able to utilize more computational power and get more accurate prediction. Please...

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Build Online Image Classification Service with Shiny and MXNetR

Build Online Image Classification Service with Shiny and MXNetR

Early this week, Google announced its Cloud Vision API, which can detect the content of an image. With the power of R and MXNet, you can try something very similar on your own laptop: an image classification shiny app. Thanks to the powerful shiny framework, it is implemented with no more than 150 lines of R code. Installing mxnet package Due to various...

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